Image Smoothing

Image smoothing aims to reduce noise and unwanted details in images while preserving important structural information. Current research focuses on improving the efficiency and quality of smoothing algorithms, particularly by leveraging techniques like iterative least squares optimization and transformer-based architectures to better distinguish between meaningful structures and irrelevant details. These advancements are driven by the need for robust and efficient image processing in applications ranging from computer vision and medical imaging to enhancing the quality of photographs and videos. The development of novel methods that incorporate semantic understanding and contrastive learning is also a significant trend, leading to more accurate and generalized smoothing results.